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davidgut1982

lore-mcp

by davidgut1982
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

investigation_log_experiment

Log structured experiments with hypothesis, methodology, results, and conclusion to document investigation findings.

Instructions

Log a structured experiment within an investigation (hypothesis, methodology, results, conclusion)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
hypothesisNo
methodologyNo
resultsNo
conclusionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed14 schema fields changedv0.8.5
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / conclusion / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / conclusion / default
      Added value: +null
    • removedInput schema / properties / conclusion / type
      Removed value: -"string"
    • addedInput schema / properties / hypothesis / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / hypothesis / default
      Added value: +null
    • removedInput schema / properties / hypothesis / type
      Removed value: -"string"
    • addedInput schema / properties / methodology / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / methodology / default
      Added value: +null
    • removedInput schema / properties / methodology / type
      Removed value: -"string"
    • addedInput schema / properties / results / anyOf
      Added value: +[
+  {
+    "additionalProperties": true,
+    "type": "object"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / results / default
      Added value: +null
    • removedInput schema / properties / results / type
      Removed value: -"object"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "result": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "type": "object",
+  "x-fastmcp-wrap-result": true
+}
  2. First observedv0.7.0

TDQS

C2.4/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, and the description provides no behavioral details (e.g., side effects, idempotency, auth requirements). It only lists parameters without explaining what the tool does beyond logging.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence front-loads the action but could be more concise or include additional context. Adequate length but not optimally structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lacks prerequisite information (e.g., how an investigation ID is specified) and does not summarize the output schema. For a 5-parameter tool, it is incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It names the parameters (hypothesis, methodology, results, conclusion) but adds no meaning beyond the property names, e.g., not describing the 'results' object structure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool logs a structured experiment within an investigation, listing components. It distinguishes from siblings like investigation_add and investigation_get, though not explicitly contrasted.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like investigation_add or investigation_delete_experiment. The context of use within an investigation is implied but not elaborated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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